Cited by 1,104Single-cell and spatial transcriptomicsGene expression and cancer classificationBioinformatics and Genomic Networks

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UCell: Robust and scalable single-cell gene signature scoring

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Andreatta, Massimo, Carmona, Santiago J.·2021·Computational and Structural Biotechnology Journal

DOI 10.1016/j.csbj.2021.06.043PMC PMC8271111

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Abstract

UCell is an R package for evaluating gene signatures in single-cell datasets. UCell signature scores, based on the Mann-Whitney U statistic, are robust to dataset size and heterogeneity, and their calculation demands less computing time and memory than other available methods, enabling the processing of large datasets in a few minutes even on machines with limited computing power. UCell can be applied to any single-cell data matrix, and includes functions to directly interact with Seurat objects. The UCell package and documentation are available on GitHub at https://github.com/carmonalab/UCell.

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Authors: Andreatta, M., & Carmona, S. J.
Affiliations: SIB Swiss Institute of Bioinformatics (CH)
Corresponding author: Andreatta, Massimo
ORCID: Andreatta, Massimo
Carmona, Santiago J.
Venue: Computational and Structural Biotechnology Journal
Publisher: American Association for the Advancement of Science (AAAS)
Published: 2021-01
Volume: 19
Pages: 3796-3798
ISSN: 2001-0370 (ISSN-L)
DOI: 10.1016/j.csbj.2021.06.043
PMC: PMC8271111
OpenAlex: W3174072032
Cited by: 1,104
References: 12
Citations by year: 2026: 355 · 2025: 337 · 2024: 255 · 2023: 111 · 2022: 39 · 2021: 6
FWCI: 36.03
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
creativecommons.org/licenses/by/4.0/ (vor, 178 d)
Locations: Computational and Structural Biotechnology Journal (publishedVersion, cc-by)
bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
SERVAL (Université de Lausanne) (publishedVersion, cc-by)
IRIS (submittedVersion, cc-by)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (180010)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Keywords: single-cell RNA sequencing, R package, computational efficiency, scalability, biological heterogeneity

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